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  1. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.1 - Deep Generative Models for Graphs [IMpkHvQ0LA4].mp4 +2 -2
  2. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.2 - Graph RNN： Generating Realistic Graphs [xGDUYQGvRac].mp4 +2 -2
  3. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.4 - Applications of Deep Graph Generation [SdBk8fMmwUU].mp4 +2 -2
  4. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 2.1 - Traditional Feature-based Methods： Node [3IS7UhNMQ3U].mp4 +2 -2
  5. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 2.2 - Traditional Feature-based Methods： Link [4dVwlE9jYxY].mp4 +2 -2
  6. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 2.3 - Traditional Feature-based Methods： Graph [buzsHTa4Hgs].mp4 +2 -2
  7. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 3.2-Random Walk Approaches for Node Embeddings [Xv0wRy66Big].mp4 +2 -2
  8. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 4.4 - Matrix Factorization and Node Embeddings [r12qJZZVtqc].mp4 +2 -2
  9. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 9.1 - How Expressive are Graph Neural Networks [5vMEgYbka0A].mp4 +2 -2
  10. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 9.2 - Designing the Most Powerful GNNs [B5y47gWt3co].mp4 +2 -2
  11. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 1.1 - Why Graphs [JAB_plj2rbA].mp4 +2 -2
  12. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 1.2 - Applications of Graph ML [aBHC6xzx9YI].mp4 +2 -2
  13. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 1.3 - Choice of Graph Representation​ [P-m1Qv6-8cI].mp4 +2 -2
  14. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 13.3 - Louvain Algorithm [0zuiLBOIcsw].mp4 +2 -2
  15. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 17.2 - GraphSAGE Neighbor Sampling [LLUxwHc7O4A].mkv +1 -1
  16. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 3.1 - Node Embeddings [rMq21iY61SE].mp4 +2 -2
  17. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 3.3 - Embedding Entire Graphs [eliMLfJeu7A].mp4 +2 -2
  18. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 4.1 - PageRank [TU0ankRcHmo].mp4 +2 -2
  19. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 4.2 - PageRank： How to Solve？ [rK2ZBmQHVVs].mp4 +2 -2
  20. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 4.3 - Random Walk with Restarts [HbzQzUaJ_9I].mp4 +2 -2
  21. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 7.1 - A general Perspective on GNNs [RU9uTa_-ZOw].mp4 +2 -2
  22. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 7.2 - A Single Layer of a GNN [247Mkqj_wRM].mp4 +2 -2
  23. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 7.3 - Stacking layers of a GNN [ew1cnUjRgl4].mp4 +2 -2
  24. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 8.1 - Graph Augmentation for GNNs [1A6VoEkQnhQ].mp4 +2 -2
  25. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 8.2 - Training Graph Neural Networks [eXIIH8YVxKI].mp4 +2 -2
  26. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 8.3 - Setting up GNN Prediction Tasks [ewEW_EMzRuo].mp4 +2 -2
  27. MLwG/Stanford CS224W： Machine Learning w⧸ Graphs I 2023 I Graph Neural Networks [ZfK4FDk9uy8].mp4 +2 -2
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